If software's been eating the world for the past twenty years, it's safe to say machine learning has been eating it for the past five. But what exactly is machine learning? Why should a web developer care? This article by Julie Kent answers these questions. I don't have kids yet, but when I do, I want them to learn two things: Whether or not you believe that the singularity is near, there's no denying that the world runs on data.
Maybe you’re interested in finding out more about deep learning? Maybe your current ML analytics are running too slowly or crushing your CPU and RAM? Or perhaps your boss has told you that they need an AI-based app so they can show off to their boss (who will then brag about it to their boss)?
Netdata contributors have greatly influenced the growth of our company and are essential to our success. The time and expertise that contributors volunteer are fundamental to our goal of helping you build extraordinary infrastructures. We highly value end-user feedback during product development, which is why we’re looking to involve you in progressing our machine learning (ML) efforts!
AI and Machine Learning are becoming critical differentiators in the technology landscape. By their nature, AI and ML are computation hungry workloads. They require best-in-class distributed computing environments to thrive. AI and ML present a perfect use case for Kubernetes, the distributed computing platform engineered at Google to run their massive workloads.
Earlier this year, I predicted that Artificial intelligence (AI) would move from innovation labs to mainstream workflow projects this year. In IT organizations, I believe service management teams will lead this trend. Here’s why.
Beginning with huge systems occupying large physical space, technology has enabled smaller, versatile devices that can be used anywhere at anytime. From the communications and hospitality industries to the public sector, either on-premises, cloud, or hybrid services were employed to make processes cost-effective.
Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. This week, we explore the concept of XAI, Explainable AI.
This blog originally appeared on HPE. Hewlett-Packard Enterprise (HPE) recently invested in OpsRamp. Consider this: when you drive a car, how would you know whether the car needs maintenance? You might look for status indicators like a check engine or change oil light. Similarly, when a pilot flies an airplane, they rely on a multitude of metrics and data to ensure the plane is running smoothly. Managing IT infrastructure is similar in nature.
